West Antarctica: still warming

The temperature reconstruction of O’Donnell et al. (2010) confirms that West Antarctica is warming — but underestimates the rate

Eric Steig

At the end of my post last month on the history of Antarctic science I noted that I had an initial, generally favorable opinion of the paper by O’Donnell et al. in the Journal of Climate. O’Donnell et al. is the peer-reviewed outcome of a series of blog posts started two years ago, mostly aimed at criticizing the 2009 paper in Nature, of which I was the lead author. As one would expect of a peer-reviewed paper, those obviously unsupportable claims found in the original blog posts are absent, and in my view O’Donnell et al. is a perfectly acceptable addition to the literature. O’Donnell et al. suggest several improvements to the methodology we used, most of which I agree with in principle. Unfortunately, their actual implementation by O’Donnell et al. leaves something to be desired, and yield a result that is in disagreement with independent evidence for the magnitude of warming, at least in West Antarctica.

In this post, I’ll summarize the key methodological changes suggested by O’Donnell et al., discuss how their results compare with our results, and the implications for our understanding of recent Antarctic climate change. I’ll then try to make sense of how O’Donnell et al. have apparently wound up with an erroneous result.

First off, a reminder for those not familiar with it: the essential innovation in our work was to combine the surface temperature data available from satellites with the ~50 years of data from weather stations. The latter are generally considered more reliable and go back a full 50 years, but are very sparse and incomplete, whereas the satellite data provide complete spatial coverage of the continent, but only since the early 1980s. We combined the two data sets by calibrating the weather station data against the satellite data, and using the calibration to get a complete spatial picture of Antarctic temperature variability and trends for the last 50 years. The key findings were that the overall Antarctic trend was positive (but not necessarily statistically significant), and that in West Antarctica, the trends were both positive and significant, especially in winter and spring. These findings were important enough for Nature to publish them because most researchers thought that significant warming was restricted only to the Antarctic Peninsula region. None of these findings is contradicted by O’Donnell et al.’s results.

O’Donnell et al. have three main criticisms of our work. First, that the reconstruction we reported was not homogenous. That is, the first part of the reconstruction (1957 through 1981) is based entirely on a linear combination of weather station data (since there are no satellite data during that period); while the second part (1982-2006) is derived simply from the satellite data. O’Donnell et al argue that it would be better to use the only weather station data for both periods, since these data are a priori considered more reliable. (There are all sorts of potential problems with the satellite data, the chief one being that there is a ‘clear sky’ bias.) That is, one wants to calibrate the data during 1982-2006, and then use that calibration to model the temperature field for both the early and the later periods, using only the weather stations.

Second, that in doing the analysis, we retain too few (just 3) EOF patterns. These are decompositions of the satellite field into its linearly independent spatial patterns. In general, the problem with retaining too many EOFs in this sort of calculation is that one’s ability to reconstruct high order spatial patterns is limited with a sparse data set, and in general it does not makes sense to retain more than the first few EOFs. O’Donnell et al. show, however, that we could safely have retained at least 5 (and perhaps more) EOFs, and that this is likely to give a more complete picture.

Third, O’Donnell et al. argue that we used too low a truncation parameter when doing the ‘truncated least squares’ regressions. In general, using too low a truncation parameter will overly smooth the results, and tend to smooth both temporal and spatial information. The problem with using too large a truncation parameter is that it creates problems when data are sparse, resulting in numerical noise (overfitting). O’Donnell et al. try to get around this problem by using cross validation — that is, trying a bunch of different truncation parameters, and using the ones that give the maximum r2, RE and CE statistics.

There are a number of other criticisms that O’Donnell et al. make, such as whether it is okay to infill the weather station data at the same time as doing the calibration against the satellite data (as we did) or whether these have to be done separately (as O’Donnell et al. did). These are more technical points that may or may not be generally applicable, but in any case do not make a significant difference to the results at hand (as O’Donnell et al. point out).

Let’s assume, for the moment, that all of these ideas are on the mark, and that the main reconstruction presented by O’Donnell et al. is, in fact, a more accurate picture of Antarctic temperature change in the last 50 years than presented in previous work. What are the implications for Antarctic climate? How would they differ what was concluded in Steig et al. (2009)? The answer is: very little.

The spatial patterns of annual trends, and how they evolve through time, is similar in both papers. In particular, O’Donnell et al. find, as we did, that the entire continent was warming, on average, prior to early 1980s (Figure below from their main “RLS” reconstruction). As we said in our paper, this would tend to support the idea that cooling in East Antarctica is a recent phenomenon at least in part attributable to recent trends in the Southern Annular Mode (SAM), which is itself forced (at least in part) by stratospheric ozone depletion.

O’Donnell et al. also reproduce our finding that the seasons in which the most rapid and significant warming is occurring are winter and spring — in large areas of both East Antarctica and West Antarctica. In spring, warming is significant throughout all of West Antarctica through the entire 50 years of the record, and in winter, it also occurs throughout all of West Antarctica in the last 25 years. In both seasons in this latter period, the locus of greatest warming has been West Antarctica, and particularly the Ross Sea region and Marie Byrd land, not just the Antarctic Peninsula as virtually all studies prior to ours had assumed. This is an important result that we highlighted in our paper because it has implications for our understanding of the dynamics involving Antarctic warming. Specifically, we made a model-data comparison in the paper, in which we said

… both in the reconstruction and in the model results, the rate of warming is greater in continental West Antarctica, particularly in spring and winter, than either on the Peninsula or in East Antarctica…. This is related to SST changes and the location of sea ice anomalies, particularly during the latter period (1979–2003), when they are strongly zonally asymmetric, with significant losses in the WestAntarctic sector but small gains around the rest of the continent.

In other words, during the period where we have good sea ice data, areas with little sea ice are always areas of surface warming in the Antarctic. It was already well established before our work that sea ice anomalies play a major role in the observed waring on the Antarctic Peninsula’s west coast. Our work showed that this is also true in West Antarctica, and is fully confirmed by O’Donnell et al.’s analysis. The only point of disagreement is in winter, in the earlier part of the record only (prior to the satellite era).

Another point of complete agreement between our results and O’Donnell et al. is that the most widespread cooling occurs in fall — not summer as discussed in earlier work (e.g. Thompson and Solomon, 2000). This may be something of a problem for the hypothesis that ozone depletion is a major driver of the observed East Antarctic cooling, because the forcing is occurring in spring (when the ozone hole develops). If there is a link between the spring forcing and fall temperature, it is not a simple one, but likely would include a role for sea ice, which offers an obvious source of persistence from season to season (a paper in review by Arnour and others argues exactly this point).

Finally, O’Donnell et al. agree with us on the most basic result of all: there is statistically significant warming in West Antarctica. In this context, it is worth being very clear on what is meant by “West Antarctica”. Reading what has been said about O’Donnell et al. in various places in the blogosphere, one would get the impression that their paper returns the warming of Antarctica to its ‘rightful’ place, the Antarctic Peninsula alone. If that were true, it would certainly be a significant refutation of our work. But in the actual abstract of O’Donnell et al., it is stated that “we find that statistically significant warming extends at least as far as Marie Byrd Land.” Marie Byrd Land is that part of West Antarctica that extends eastward from the Ross Ice Shelf up past Byrd Station and over the central West Antarctic Ice Divide (see the map above). In O’Donnell’s results, there is significant warming all the way from the Peninsula westward past WAIS Divide site, at 112°W, well within Marie Byrd Land and nowhere near the Antarctic Peninsula. Prior to our work, no one had claimed that any area outside the Peninsula was warming significantly. Borehole thermometry at WAIS Divide (Orsi and Severinghaus, 2010) and at the Rutford Ice Stream (closer to the Peninsula; Barrett et al,. 2009) has since provided completely independent validation of these results. O’Donnell et al. is thus merely the latest of several studies to confirm our original finding*: West Antarctica is warming significantly.

To be sure, there is real disagreement between our results and those of O’Donnell et al. For the full fifty year reconstruction of temperature trends, the main reconstruction they discuss in the paper shows cooling in the winter and fall over the Ross Ice Shelf, which contrasts with our finding of significant warming there. As a consequence, their overall warming trends are smaller, by about half. These are the only important differences between our results and those of O’Donnell. Nevertheless, they are significant differences, and certainly may be important for our understanding of Antarctic climate change. In particular both results would tend to suggest a greater role for natural variability than our findings implied. If O’Donnell et al.’s results are correct, this would suggest that the damped response of Antarctica to global radiative forcing (i.e. CO2 increases) that is commonly seen in models (as discussed previously by Spencer Weart, for example) is perhaps more on the mark than our paper would suggest (though note that even the much larger trends we estimated are still significantly damped compared with the Arctic.)

Let’s return now to the question of whether O’Donnell et al.’s results actually do represent an improvement over ours. The figure below indicates a rather glaring problem: O’Donnell et al. disagree markedly with the raw weather station data from Byrd, which is the only record of any length anywhere in West Antarctica. Shown in the figure, reproduced again below, are the main reconstructions of Steig et al. (2009) (green) and O’Donnell et al. (2010) (blue), compared with the the actual raw data (black) from the Byrd weather station. The simple linear trend on the raw data is nearly four times larger in reality than shown by O’Donnell et al., whereas it is not statistically distinguishable from Steig et al. There are a lot of missing data from Byrd (and annual means in the figure include some missing months), so also shown in the figure (dashed) is an independent infilling of missing data from Byrd station, done by Andy Monaghan (using no satellite data whatsoever, as described in Monaghan et al., 2008, plus new data available through 2009). The updated Monaghan estimate — currently under review — indicates an even higher trend, >0.4°C/decade, when the data are updated through 2009.

The evident failure of O’Donnell et al. to correctly capture what is going on at Byrd (and presumably elsewhere in West Antarctica) is quite surprising, given that one of key differences in their methodology is to use the weather station data — not the satellite data as we did — as the verification target. That is, O’Donnell et al. use weather stations, withheld one at a time from the reconstruction for verification purposes to optimize their calibration. How then, can they be so far off for the location of the most important weather station? (I say ‘most important’ here because the main point of contention is, after all, West Antarctica). There are three likely sources of the problem, each pertaining to O’Donnell et al. implementation of their suggested modifications to the method we used.

First, as I noted above, O’Donnell et al. use a linear combination of weather station data for their reconstruction, both in the reconstruction period (pre-1982) and in the calibration period (the satellite era, post 1981). This is a very reasonable thing to do, resulting in a more homogeneous data set than ours. However, it also means throwing out information that might be important: namely, that there are strong trends in the temperatures in West Antarctica that may not be captured by any weather station data. This is not a very large problem in East Antarctica, where the scale of spatial covariance is large, and the number of weather stations is also large; it is a potentially huge problem in West Antarctica, where the number of stations is small (again, only Byrd goes back beyond the satellite era) and the spatial scale of covariance is also smaller, due to the greater topographic relief. On top of that, O’Donnell et al. do not appear to have used all of the information available from the weather stations. Byrd is actually composed of two different records, the occupied Byrd Station, which stops in 1980, and the Byrd AWS station which has episodically recorded temperatures at Byrd since then. O’Donnell et al. treat these as two independent data sets, and because their calculations (like ours) remove the mean of each record, O’Donnell et al. have removed information that might be rather important. namely, that the average temperatures in the AWS record (post 1980) are warmer — by about 1°C — than the pre-1980 manned weather station record. Note that caution is in order in simply splicing these together, because sensor calibration issues could means that the 1°C difference is an overestimate (or an underestimate).** Since Steig et al. retained the satellite data, we didn’t need to worry about this. O’Donnell et al didn’t have that luxury, and should at the very least have considered the impact of treating Byrd Station and Byrd AWS as entirely independent records.

Second, in their main reconstruction, O’Donnell et al. choose to use a routine from Tapio Schneider’s ‘RegEM’ code known as ‘iridge’ (individual ridge regression). This implementation of RegEM has the advantage of having a built-in cross validation function, which is supposed to provide a datapoint-by-datapoint optimization of the truncation parameters used in the least-squares calibrations. Yet at least two independent groups who have tested the performance of RegEM with iridge have found that it is prone to the underestimation of trends, given sparse and noisy data (e.g. Mann et al, 2007a, Mann et al., 2007b, Smerdon and Kaplan, 2007) and this is precisely why more recent work has favored the use of TTLS, rather than iridge, as the regularization method in RegEM in such situations. It is not surprising that O’Donnell et al (2010), by using iridge, do indeed appear to have dramatically underestimated long-term trends—the Byrd comparison leaves no other possible conclusion.

O’Donnell et al. do not rely entirely on ridge regression. They also present results from a more explicit cross-validation test, using various truncation parameters for a ‘truncated total least squares’ (or ‘truncated singular value decompositon’) regressions, as we did in our work. However, these tests, as implemented, are also problematic. O’Donnell et al. actually use cross validation in two steps: first, by filling in missing data in the weather station records and choosing the truncation value (kgnd) that yields the best overall verification statistics. Second, by reconstructing the entire spatial field with another truncation value, ksat. In both cases, the optimization is done on the basis of the entire data set; that is, the ‘best’ parameter depends on what works best on average both in data poor regions (e.g. West Antarctica) and data rich regions (e.g. East Antarctica and the Peninsula). The obvious risk here is that too high a truncation value will be used for West Antarctica. There is rather good evidence to be found in the Supplementary Material in O’Donnell that this is exactly what has happened. The choice of kgnd that yields the best agreement with the iridge calculations (which, remember, is already known to create problems) happens to be kgnd = 7, and it just so happens that this yields the minimum trends. In fact, O’Donnell et al. show in a table in their Supplementary Material that the mean trend for West Antarctica for smaller values of kgnd is more than twice (~0.2 °C/decade) what it is for their ‘optimum’ estimate of kgnd = 7 (~0.07°C/decade). Indeed, using any value lower than the one they choose to rely on largely erases any difference between their results and Steig et al., 2009. This simple fact — illustrated in the figure above (trends in °C/decade for 1957-2006) — has been notably absent in the commentaries that O’Donnell and coauthors have made about their paper.

Third, the way that O’Donnell et al. actually do the cross-validation to optimize ksat is itself pretty dodgy. Rather than using split calibrations (that is, comparing early period with late period statistics), they one-by-one withhold each weather station time series over the entire length of the record. To see the problem with this, consider what happens if you withhold the South Pole station record, which is complete for the entire time period, and then repeat the regressions to find the best truncation value for South Pole. For the period 1982-2006, when there are satellite data available for (and highly correlated with the station at) South Pole, the optimal number will be much higher (data richness) than during the pre-satellite era (data poor). The number that gets used will be an underfitting for the pre-satellite era and an overfitting for the satellite era. Note that ksat is actually the number of EOFs that get retained; since one needs many more of these to reconstruct the Peninsula properly, it is inevitable that they’ll wind up with more retained EOFs than we did; that doesn’t mean this is the right number for West or East Antarctica. O’Donnell et al. do report split calibration statistics as well, but this is not how they choose their optimal values.

Does all of this mean that I think O’Donnell’s results are all wrong? Certainly not. I think that they are right to have retained more EOF patterns than we did, though the main impact of this is only in capturing the strong Peninsula warming.*** It is also quite likely that O’Donnell et al.’s results are more accurate than ours for the satellite era, during which most of the problems I have discussed above are less likely to arise. Although their results show much smaller trends, they agree well with the spatial patterns in weather forecast reanalysis data products (NCEP2, ERA-40) during the satellite era. This is a nice, largely independent validation of those products, and suggests that it is okay to use those products — which include detailed information on atmospheric circulation changes, for example — for investigating the causes of the temperature trends. This is something that quite a few of us have been working on, but there has always been the nagging problem that we don’t really know how much we can trust NCEP and ERA products at high southern latitudes. O’Donnell et al. should certainly be cited in support of such work.

In summary, even if their results are taken at face value, O’Donnell et al. 2010 doesn’t change any of the conclusions reached in Steig et al. In West Antarctica where there is disagreement, Steig et al, 2009 is in better agreement with independent data, and O’Donnell et al.’s results appear to be adversely affected by using procedures known to underestimate trends. Thus while their results may represent an improved estimate for the trends in data rich regions — East Antarctica and the Peninsula — it is virtually certain that they are an underestimate for West Antarctica. This probably means going back to the drawing board to write up another paper, taking into account those suggestions of O’Donnell et al. that are valid, but hopefully avoiding their mistakes.

*Contrary to what Ryan O’Donnell has claimed, Doran et al. (2006) reported warming in Ellsworth Land (between WAIS Divide and the Peninsula) only in winter, with cooling in the annual mean. It is worth noting that Doran’s work has previously been misrepresented, though in the opposite way!

**There is, however, completely independent data from the WAIS Divide borehole, showing that this site has warmed by the same amount indicated by the Byrd weather station data — about 1°C since 1958. This is unpublished data, but the results were presented in an AGU talk and in the published abstract.

*** Peninsula warming was not the question we were addressing in our paper, as we made very clear in the text. We chose fewer EOFs based on our previous work (Schneider et al., 2004) showing that this sufficiently captures both East and West Antarctica.) Although retaining fewer EOFs reduces the spatial details, it is a conservative choice for estimating large-scale trends in both West and East Antarctica. See also our discussion on overfitting.

Interesting stuff, thanks. Do you intend to write the updated paper you mention at the end Eric?

[Response: At some point, yes. It’s not very inspiring work, since the answer doesn’t change, but i suppose it has to get done. I had hoped O’Donnell et al. would simply get it right, and we’d be done with the ‘debate’, but unfortunately not.–eric]

What factors are likely to be causing the Peninsula and West Antarctic warming? Previous articles and postings point to Southern Storm Track changes and intensification of individual storms. Sea surface temperature increases have also been implicated. Is there a role for aerosols as well?

[Response: Dave Schneider has a new paper in press on this, but it only explains what’s happening in Spring for West Antarctica. It’s in press in Climate Dynamics (here). Conventional wisdom is that intensified westerlies (Southern storm track, as you said, or the ‘Southern Annular Mode’) is driving Peninsula warming, but that explains at most half the story, and doesn’t explain why it has been happening for 100 years. I doubt aerosols are important here (air in Antarctica is pretty clean!). There is more work to be done, clearly.–eric]

I haven’t followed this issue in much detail but it’s interesting that a large degree of what’s going on in Antarctica isn’t just radiative but highly dynamical. Hopefully someone who knows what they are talking about chimes in but the variability in the high-latitude SH is influenced strongly by the SH annular mode (i.e. related to anomalies in the strength of the circumpolar vortex, the local tropospheric circulation). There’s been work showing that the decline of stratospheric ozone since the late 1970s may account for some warming in the peninsula region in the SH autumn and summer, which is linked to a positive trend in the Southern Annular Mode. This doesn’t really warm the Antarctic peninsula and there’s a mis-match in the seasons of predominant West antarctic warming and trends in SAM. There is a paper in pressreview from authors at UWashington (including Dr. Steig) that relates the warming to teleconnections between the Antarctic region and sea surface temperature anomalies in the Pacific. See Lachlan-Cope, T. & Connolley, W. Teleconnections between the tropical Pacific and the Amundsen-Bellinghausens Sea: Role of the El Niño/Southern Oscillation, J. Geophys. Res. 111, D23101, (2006) for an interesting mechanism.

I don’t know a whole lot about the underlying dynamics here, but I think it’s neat. It also helps to think about how the global trend which is always radiative-forced is a lot easier to think about than regional trends! Presumably as the central tropical Pacific should keep warming those dynamic linkages would allow for persistence in the West Antarctic, but ozone recovery will matter too for other regions.

“… The primary sources for the observed iodine enrichment are likely to be biogenic processes in the ocean, but possibly also at the bottom of the sea ice which is a habitat for various algae species which are potentially emitting iodocarbons. However, it still remains unclear how the strong accu-
mulation of iodine on the snowpack occurs. Furthermore, it can only be speculated about the transport pathways of short-lived iodine compounds from the coast to inland Antarctica….
…
… IO present at these extraordinarily high concentrations in the snowpack interstitial air and in the atmosphere near the surface of the Antarctic shelf ice at Neumayer Station is expected to have a significant, if not dominating impact on photochemistry…. The formation of higher iodine oxides is likely to lead to the production of ultrafine particles….”

I stumbled over that paper after reading about increases in iodine in the Arctic from warming.
——
The reCaptcha AI awakens: “Iodogen mbfort”

I don’t have access to the O’Donnell et al paper. Does it state in the text that they use RegEM’s ‘iridge’, or does it include source code?

[Response: Yes, and yes. You can get O’Donnell’s code: here. You can also get the Supplementary Material, from which I got the last figure in this post, showing what happens when you use O’Donnell’s methodology but other values of their k_gnd. If you can get their code to work properly, let me know. It’s not exactly user friendly, as it is all in one file, and it takes some work to separate the modules.–eric]

Mr. Chris Colose writes on the 1st of February, 2011 at 12:56 PM :
“…a large degree of what’s going on in Antarctica isn’t just radiative but highly dynamical.”

I entirely agree, and would like to extend the statement: the important dynamics is in the warming oceans and the ice shelves and streams. This is slightly reminiscent of the situation in Greenland, except that as many have noted, Greenland glaciers can retreat for a time from the ocean, but Antarctica, both East and West have vasty deeps beneath where the ice is vulnerable. The ocean can deliver heat far faster than the air both as warmwater currents under the ice shelves, and rain as in Greenland. When I see reports of regular rain in East Antarctica, I shall know the end is nigh, and don my bathrobe and sandwich board.

sidd

[Response: I wouldn’t count on much rain in East Antarctica for some time there. I’ve been rained on in McMurdo of course….–eric]

J – If you overlay the volcano locations on the Antarctic warming, there is significant warming where there aren’t any volcanoes, and cooling where there are volcanoes, and warming and volcanoes only at the tip of the Antarctic peninsula. Occam would say they aren’t correlated.

[Response: Sigh…. I’d put this in the “Bore Hole”, but perhaps one of our readers wants to explain something about the difference between watts/m^2 and milliwatts/m^2? [hint: I frequently ski on volcanoes; how the heck does the snow stay up there?] It might provide an object lesson, not to mention show why ‘jeffifermarohasy.com’ is not a credible source for anything.–eric]

“perhaps one of our readers wants to explain something about the difference between watts/m^2 and milliwatts/m^2?”

A few pictures are worth thousands of words:

Here’s a plot of geothermal heat flow. Note that the scale is in milliwatts per square meter, and that the highest levels are from ocean ridges, and most of Antarctica is less than 85 mW/m^2.

Here’s a plot of outbound longwave radiation. Note that the scale is in Watts per square meter, and that everything outside the 120 W/m^2 contour around the middle of Antarctica is more than 1000 times larger than the 120 mW/m^2 geothermal heat flux at the tip of the Antarctic Peninsula from the first image.

Are you saying that there has been a surge in volcanic activity concurrent wioth the observed warming? I claim with an equal amount of evidence that there has been a significan decline in volcanic activity which has attenuated and masked the warming caused by GHG emissions.

A new paper with refined methods and four more years of data sounds very worthwhile to me. “It’s not very inspiring work, since the answer doesn’t change….” Surely it will change some, and this change and its rate matter.

I think you are making the mistake of misunderstanding the resolution to which these methods can be taken. You are looking at patterns in spatially autocorrelated data sorted by PC’s and making conclusions from them. IMO (from a lot of time spent) the small regions you are looking at are beyond the capability of these methods.

If your work happened to match the ‘trend’ of an expected region better than ours, it is only by pure luck as the data from S09 is simply smeared around – as can be seen from the low correlations and over representation of seasonal peninsular information across the continent. Our version just smears it around less. For instance, I don’t believe the little finger of warming from the peninsula into the continent we show is anything other than the boundary (node) of the eigenvectors that happens to visually follow the mountans, it could be true but how do we know?

If you really want trends for the Antarctic, I would humbly suggest just using the temperature station data that is available. Perhaps infilling using offset method provided on Roman’s statpad site. The satellite information provides little additional value for spatial distribution and only additional error for trend.

Of course that is just my opinion, my coauthors may feel differently. Ryan and Nic put a lot of time into investigation of different methods for improvement. As optimized as our results are, the process very clearly showed that these EM methods are limited and can lead to improper conclusions on small and large scales as well as large errors in result.

BTW, using closest station infilling with proper anomaly alignment should give you the satisfactory amount of warming for the West Antarctic you are looking for and is basically very difficult to argue with. The SI version didn’t make the cut through the review process.

[Response: It is a bit strange that your coauthors have spent so much time talking about the differences in the Ross Sea region, as if this somehow ‘refutes’ our work, and now you are saying that the methods simply can’t resolve such small areas. Whichizzit?

I think that one of the things that many readers will take away from your work is that these methods are simply too sensitive to parameter choices to be able to say anything. That’s Kevin Trenberth’s unhelpful comment when my paper came out: “It’s hard to obtain data where none exist” or something like that.” The problem with that — besides being demonstrably untrue — is that without these sorts of analyses, all that’s left is ‘interpolation by eye’, which is what everyone was doing for West Antarctica prior to our work. And to be clear again, a main point of my post is that you have *not* optimized the results properly. Our results can certainly be improved on, but unfortunately I don’t think you have been successful in doing that. As for the distance-weighting calculations, I agree that’s a reasonable thing to do, but the point of our paper was to use the *additional* information about spatial relationships that the satellite data provides. I think this is useful, and I think that your paper — with its very good agreement during the satellite era with weather forecast reanalysis products (NCEP2, etc.) demonstrates this very nicely. Cheers — eric]

Eric writes : “our work was to combine the surface temperature data available from satellites with the ~50 years of data from weather stations. The latter are generally considered more reliable and go back a full 50 years”

Would you mind explaining this? I was under the impression that many of the ground based stations were extremely problematic, continually breaking down and being covered in snow and ice.

Whereas satellite measurements, whilst having their own problems, are at least consistent and more likely to give reliable trends.

[Response: Ray makes a bunch of good points below on this. The major problem with the infrared satellite data is that it can’t see through clouds, so a lot of work goes into trying to mask out cloudy days. If it is getting cloudier as it gets warmer, then you’ll mask out more and more clouds over time, and damp the warming trend. That assumes that you have done your cloud masking correctly of course. It’s also true, however, that it is generally an *assumption* that the ground-based records are more reliable; there’s not much proof. Note that we did not use the automatic weather stations, which are the really problematic ones since there is no person regularly attending them (though in fact you get the same result from them as from satellites). –eric]

I take it from your comment that you have never had to use satellite data. First, there is the problem that most space missions are short on climatic timescales. Even the longest Earth-orbiting missions are of order a decade. This means that of necessity to obtain a record relevant to climate, you must splice together 3 or datasets from different instruments on different birds.

Second, the space environment is both nasty and dynamic. So your sensors themselves are always changing–degrading in the radiation environment or from extremes of temperature or simple aging. On the ground, when a sensor starts to age, you replace it. In orbit, you live with it.

Third, satellites are VERY expensive. This means there are never enough to give you all the measurements you want AND that instruments are always multi-purpose compromises. Oh, and launching a Coke can into orbit costs ~$10000, so your instrument better be tiny and light.

Fourth, there are no housecalls to satellites. You live with the performance the instrument gives you, and you can’t really tweak it to optimize performance.

Fifth, you have about 100 miles of atmosphere between you and what you are trying to measure, so you will always have distortion.

Sixth, a spaceborne instrument never measures quite what you want. For instance, you can’t measure temperature, so you have to measure brightness in a particular spectral band. You can infer temperature, but the results will always be model dependent.

I could go on…and on and on and on. However, that gives you some idea.

I agree with you that ” it’s interesting that a large degree of what’s going on in Antarctica isn’t just radiative but highly dynamical.”

I only want to add that the radiative and dynamical aspects are coupled with each other, and even on global average the dynamical feedback can contribute to the warming directly or indirectly. On regional scale the radiative fluxes at the TOA can not be balanced by themselves, but have to be balanced by in(out)-put dynamical energy transports. Maybe it is better to distinguish them by local and non-local.

[edit — details of our paper aren’t really appropriate to get into at the moment, as it is still in review –eric]

Eric writes : “If it is getting cloudier as it gets warmer, then you’ll mask out more and more clouds over time, and damp the warming trend.”

Are you now suggesting there is a 30 year cloud cover trend present over Antarctica? That would be a significant result in itself and until it is known one way or the other, then speculating on its existence would seem premature.

[Response: No, of course not. I’m just giving a ‘what-if’ example to explain how the trends might be affected. Of course, if it is getting warmer, it is because of warm air advection, and in West Antarctica that typically means cloudier, so there probably *is* a trend in cloudiness. However, we’ve looked at this and it does not appear to be very strong.]

Assuming that Earth based temperature sensing in the Antarctic gives a better *trend* seems unsupportable to me given the known problems with earth based measurement.

Ray regarding “Second, the space environment is both nasty and dynamic.”

Seems irrelevent to the point at hand. Do you believe satellite based measurement will give a better trend for warming over the Antarctic continent or not?

Finally to Eric and others, are you aware of any “satellite only” analyses of Antarctic warming?

[Response: This isn’t a matter of ‘belief’, it is a matter of evidence, and the evidence at hand doesn’t really allow us to answer the questions you are posing. We don’t know. As for analyses with satellites only, sure, there are many. Start with Comiso, 2002, in the Journal of Climate. The results are not substantially different from ours. The reason our analysis — and O’Donnell et al.’s — works at all is that there is high correspondence in both interannual variability AND trend in both the satellite data and the ground station data.–eric]

#20–Thanks for a nice (if apparently incomplete) summary. I know some folks who apparently believe that satellite data is perfect upon initial download–as well as that the UAH analysis of same is perfect, too.

Thank you for the impressive amount of detail in explaining the differences and commonalities between your and O’Donnell’s reconstruction of Antarctic temps and West Antarctica in particular.
I must say some of the statistics go a bit over my head, so please forget my simplistic assessment below.

First off, I understand that you conclude that the main difference in the two reconstructions is in the interpretation from the weather data from one station (Byrd). O’Donnell reconstructs a lower trend than you do, as you point out in the graph.

I don’t understand all the issues involved in reconstructing and calibrating that station’s record (or the Byrd AWS record next door), but the thing that troubles me is your remarks that Byrd \is the only record of any length anywhere in West Antarctica\ and your subsequent remark that
\only Byrd goes back beyond the satellite era\.

If the temperature reconstruction from before 1980 for all of West Antarctica is based on the record of a single station, which apparently also contains \lot of missing data\, then you can work with statistics whatever you (or O’Donnell) want, but common sense would tell me that you cannot possibly derive any conclusions for temperature trends for the whole of West Antarctica from that.

If you would discard the Byrd station data altogether, would you (or O’Donnell) still be able to claim anything about the temperature trends in West Antarctica before 1980 ? And if not, then are you both not walking a very thin line when claiming that West Antarctica is warming ‘significantly’ ?

[Response: Temperature variations change over characteristics spatial scales. Those spatial scales are not infinite, but they are not zero either. Our calculations are estimates based on information about that spatial scale taken from the satellite data.–eric]

Thanks for the reference to the Comso paper, but as far as I can see it doesn’t have anything to do with warming trends in the sense I was interested in.

It states “The objective of this study is to explore the spatial details in the teleconnections between SO and the anomalies in the Southern Ocean climate and in particular the anomalies of the Antarctic sea ice cover.”

To be fair, I guess you did say “start with” though.

Eric writes : ” The results are not substantially different from ours.”

According to the IPCC AR4, the Comiso paper finds that recent decades are associated with “cold anomalies over most of Antarctica”

Specifically it says this, “The positive phase of the SAM is associated with cold anomalies over most of Antarctica and warm anomalies over the Antarctic Peninsula (Kwok and Comiso, 2002a). Over recent decades, a drift towards the positive phase in the SAM is evident”

How can you interpret the IPCC’s assessment of their paper, “cold anomalies over most of Antarctica” as being “not substantially different from ours” when yours finds warming over most of Antarctica?

[Response: Tim, what is your point here? That I don’t know what I’m talking about? Or that you haven’t read either my paper or O’Donnell’s? None of your questions make any sense if you’ve read our work. To be clear: Comiso’s estimates of the temperature trends at the time of that work were based on a much shorter time period, and his cloud masking routine, which was later refined, evidently produced unrealistically large warming trends and cooling trends. His updated work agreed much better with the weather stations. This is all discussed in our paper.–eric]

TimtheToolman,
On the space environment and its effect on satellite records, perhaps I need to be more clear. Radiation and other strains of the space environment cause sensors to degrade fairly rapidly. The more sensitive the sensor, the more rapid the degradation. As such, this limits not just the lifetime of the sensor, but the type of sensor one can fly and how well calibrated it is over its mission. In addition, there are single-event effects (cosmic ray strikes) that introduce noise into sensor measurements or which may invalidate chunks of data.

As to whether ground-based or land-based is better…you need both. They are complementary. However, if there is a problem with an instrument, it’s a whole lot easier to do something about it on the ground–even in Antarctica–than it is in space. What is more (although this is not true in Antarctica), oversampling can make the groundbased record much more reliable.

Ray : “On the space environment and its effect on satellite records, perhaps I need to be more clear.”

No you dont need to be more clear. You are arguing that gradual degredation of satellite sensors is more problematic than sporadic icing over of temperature sensors, breakdowns and extreme sparseness of sensors in the East Antarctic interior.

[Response: Please stay civil, both of you. Tim, your points are valid about icing sensors etc. Ray is being a bit pedantic and overstating the problems with satellites, but he’s not entirely off base either. Bottom line is that measurements in extreme environments are difficult and their are problems with *both* these tools. Hence the importance ;) of both Steig and O’Donnell’s work to try to use information from both. –eric]

Eric, thank you for your response.
I understand that the post-1980 satellite data provides the spacial scales over which area the data from a weather station can be considered relevant.

However, my concern is with the fact that the Byrd station is the ONLY station data available in West Antarctica before the satellite era, and that your assessment of significant warming (before 1980) is based (only?)mostly on that one station.

I just imagine the scenario that the guy who was in reading the Byrd thermometer back in the 1950’s may have had a habit of rounding down between the resolution lines on the analog thermometers (probably in the range of a few tens of a degree), and that his human emotional bias of “see how much I’m suffering here in the mids of winter” now shows up on the front page of Nature as evidence that West Antarctica is warming..

Please do not get me wrong, I am a scientist myself and in great admiration of what climate scientists are accomplishing in the face of intense critisim from non-scientific sources. Still, you should admit that a single data point (although better than none) is not a good basis to draw any ‘significance’ conclusions for half a continent, and you would actually turn me into a ‘skeptic’ if you would think otherwise. Especially since trend dispute (0.1 C/decade) that you and O’Donnell talk about are an order of magnitude smaller than the standard deviation in the Byrd data (which seems to be in the order of 1 C).

In that regard, can you please address my question more directly : If you would discard the Byrd station data altogether, would you (or O’Donnell) still be able to claim anything about the temperature trends in West Antarctica before 1980 ? And if not, then are you both not walking a very thin line when claiming that West Antarctica is warming ‘significantly’ ?

[Response: If you discard Byrd, you still have covariance information with all the other stations. As O’Donnell et al. say in their paper, their results don’t actually depend much on Byrd. However, I agree that without any data Byrd, both our results and O’Donnell’s would be at *subjectively* less compelling. Whether they would be *objectively* less compelling depends on the goodness of fit of statistics, and whether the those statistics are stationary. With no stations for verification in West Antarctica, it would be impossible to test stationarity, but one could still put confidence levels on the calculations with the caveat that stationarity is assumed. The reality of course is that we do have Byrd, we also have the borehole data, and we have the fact that very minor changes to the parameter choices made by O’Donnell et al. are in better agreement with those independent data sources.–eric]

TimTheToolMan,
If a sensor ices over, it will eventually thaw. (Note temperature control can be a significant issue for satellites as well.) If it breaks, you can replace it on a timescale of months and a cost of a few thousand dollars. It will also be obvious that something is wrong with it.

You can count on none of these things with satellite data. If a satellite loses thermal control, you lose the bird. If the instrument breaks, game over. And replacing it will take 4-10 years and cost millions.

I am not saying satellite data are not useful, but they complement rather than replace ground measurements.

[Response: Yes, but Ray, the satellite data *we* used didn’t break down. We have 30 years of continuous records now. You’re greatly overstating the problems.–eric]

Eric,
I appreciate your honesty in confirming the influence of the Byrd station as pivotal in the determination of ‘significance of warming’ for West Antarctica in the 50 year reconstruction. Also, I find it admirable of you to mention not just your critisim of the methods used in O’Donnells findings, but also the common conclusions, and the benefits of their methods (more accurate during the satellite era, and confirmation of the NCEP and ERA product data).

Your honest and scientific analysis of the O’Donnell findings is a relief compared to the overblown ‘victory’ reports of the O’Donnell paper on the ‘contrarian’ web-sites, where O’Donnell’s paper was hailed as a ‘debunking’ of your findings.

In the end, since the conclusions from you and O’Donnell are not really far apart at all, I think that the actual warming rate of West Antarctica is in effect marginally important.

In all, I found yours and O’Donnell’s papers facinating, not just because both your papers find consistent results that West Antarctica is warming, but because (for an outsider like me) it shows how little the results differ between two teams that are obviously in competition with each other.
Thus, it shows that skepticism in climate science is alive and well, and in that regard, your hard work to defend your findings and put perspective on the differences with O’Donnell’s work are more significant for public perception than you may want to believe. For me personally, thank you for the perspective, since I’ll be more informed when debating with ‘skeptics’ on the contrarian web sites (which is what I do in my spare time).

Belated congratulations on your Nature publication, thank you for your post, and please keep up the good work. Incidentally, what will be your next subject of research ?

As for next line of research well, we have two or three independent data sets that demonstrate the significant warming at Byrd is real and widespread, a couple explaining the origin of the Antarctic Peninsula warming, and a few other things. The major thing, however, is the new deep ice core which we just completed drilling to 3331 m. –eric]

Rob (#29) says: \Please do not get me wrong, I am a scientist myself and in great admiration of what climate scientists are accomplishing in the face of intense critisim from non-scientific sources. Still, you should admit that a single data point (although better than none) is not a good basis to draw any ‘significance’ conclusions for half a continent, and you would actually turn me into a ‘skeptic’ if you would think otherwise. Especially since trend dispute (0.1 C/decade) that you and O’Donnell talk about are an order of magnitude smaller than the standard deviation in the Byrd data (which seems to be in the order of 1 C).

I’m with Rob all the way on this. His is the only blog comment so far in this trail that brings us smack up against reality: How on earth can people be arguing (one way or the other) about a trend of the order of 0.1degC/decade when the data has a standard deviation of the order of 1degC? It just defies all common sense.

C’mon all you guys, we are in danger of having a fierce (although pleasingly polite) discussion about how many angels can dance on the point of a needle – when what most people out there want to know is whether there is any evidence at all that the Antarctic has warmed overall over the past half century. Answer not significantly – so end of (important) story, surely?

[Response: You are making a fair enough point — that O’Donnell and I seem to be arguing about seemingly unknowable thing, but note that your estimate of the trend and variance is off by a factor of five. The variance is indeed 1, but the trend about 0.4, significant at p< .001 --eric]

Eric, My intent is not to denigrate the importance of satellite data. Far from it. It is absolutely essential. Rather, my intent is to highlight the fact that even when things go perfectly, satellite data are not easy to interpret. That is true whether your instruments are pointed at Earth or at a gamma-ray burst.

In any Earth-related observation, terrestrial data will complement satellite data, and each will pose their own difficulties. Scientists know how to use imperfect data, regardles of its source. The question is how long some poor grad student or post doc is going to have to sweat over the data to make sense out of it

I have concentrated on the difficulties of interpreting satellite data becuase 1)I work on satellites in my day job; 2)Tim was saying the satellite data were of necessity better and more reliable. I’m merely sayin’ “‘Taint so.” My goal when I am working on a satellite is to keep the poor grad stuedent’s from consigning me to perdition more than about once a month.

Eric says (response to my #33): You are making a fair enough point — that O’Donnell and I seem to be arguing about seemingly unknowable thing, but note that your estimate of the trend and variance is off by a factor of five. The variance is indeed 1, but the trend about 0.4, significant at p less than 0.001

Thanks for you interesting reply. But in fact it was not me but Rob who asserted that both you and O’Donnell talk about a trend dispute of 0.1degC/decade. It would be interesting to hear from Rob why he used that figure and whether he now accepts your much larger trend figure of 0.4degC/decade.

[Response: Whatever — you said “I’m with Rob all the way”. Anyway, Rob is right — the *dispute* is about 0.1°C, because both sets of calculations underestimate the real actual observed trend.–eric]

The south pole during Antarctica’s polar winter provides a great contrast to the wind and temperature asymmetries generated by oscillations on the peninsula and west Antarctica . During the south pole winter without incoming shortwave radiation, there is a steady cooling as longwave radiation exports energy. Surprisingly from the end of March to the end of July the temperatures do no drop more than 2 degrees C. This is because an upper level supply of warm air is advected poleward. Due to the inversion layer of cold stable air their is insignificantly little vertical mixing at the pole. Thus the heat budget during the winter at the south pole is relatively the most simple to analyze Using the temperature data from Amundsen-Scott we see there is a heat budget equilibrium from March thorugh August which varies for the years 1955 to 1976 from -55 to -57. From 1977-2010 those winter lows have dropped -2 C on average- varying from -57 to almost -60.

If CO2 was increasingy holding more heat in the cold air mass at the pole it should be warming. If the poleward advected air mass held more moisture or CO2, it should be warming. The cooling trend also would suggest that the cooler air might move coastward more quickly and thus draw in a greater amount of upper level warm air to to replace the colder air flow towards the coast , but in contrast it is still cooling. The southpole winters suggest something very different is affecting it that overpowers any possible CO2 attribution.

Using south pole cooling trend as a background heat budget,the rising temperatures in the west Antarctica can on;y be attributed to changes in asymmetrical heat distribution through oscillations such as the SAM, etc

[Response: Yes, dynamics dominates; I agree with you entirely there. But using South Pole radiative budget as a way to estimate the heat budget everywhere else is problematic. That is, don’t conflate South Pole with all of Antarctica. CO2 is globally quite well mixed, so this isn’t in question. As you said (but I’m just trying to make it a bit clearer here), the question is whether dynamics (air mass advection) or other radiative influences (e.g. ozone) overwhelms it. I agree that at South Pole, it obviously does, and I think this is also the case for West Antarctica, but the argument doesn’t follow directly from the South Pole observations. Our original paper makes it very clear that we think it is dynamics, and we articulate a mechanism. A major point we make is that the structure of the dynamical changes in wave-3 like, not wave-1 like. That is, it’s not the SAM.

Note that SAM has no trend in winter or spring, so this obviously cannot account for the winter cooling at Pole. Incidentally, the the ‘cooling trend’ at Pole has never been statistically significant and is now gone, at least in the annual mean. In fact, the 1st or 2nd warmest summer on record at South Pole is 2009 or 2010 last time I checked (though 1958 or 1959 may be warmer, slightly). –eric]

I am curious what you think would cause the south pole’s winter cooling trend. I agree it is not likely SAM related. I also doubt it is ozone related as correlations seen with ozone and coastal temperatures are not similarly observed at the pole or McMurdo or Halley stations. I am also sure that a statistically significant cooling trend is absent for the annual trend although that may depend on the time frame, but at the pole for the winter months it appears quite significant. The warm summers you mention are undoubtedly related to advection and disturbed vertical motions that are connected to the SAM. But I hesitate to read to much into such short term jumps since much of Antarctica is subject to foehn wind storms that can lead to 30+C rises within 24 hours.

The only similar cooling trend I observe is the declining solar trend since 1959.

[Response: I don’t know what the answer is to the winter cooling — I agree it is statistically significant. There is probably some literature on this, but I’ve not looked into it much. We actually talk about this a bit in our 2004 paper in J. Climate (Schneider, Steig and Comiso), but only indirectly (look for the stuff on ‘blocking events’). More work needs to be done on this, for sure! (And the sun is a total red herring of course — remember, there is no sunlight in winter in Antarctica, and in general the lure of solar forcing usually turns out to be of dubious merit.)–eric]

Ray writes : “Tim was saying the satellite data were of necessity better and more reliable.”

And I maintain satellite data is MUCH better and more reliable in the context of this conversation. And the context of this conversation is determining temperature trends in Antarctica.

None of your points even *begin* to compare to the problems and shortcomings of the Antarctic land based measurements. As others have stated, pre-satellite data includes just ONE station upon which the result hinges. And that station has problems of missing data and icing over of the thermometer.

One last thought. Although many cooling trends elsewhere can be attributed to changes in the wind directions and thus source of winds ie land vs ocean, I think that the cooling trend at the south pole would a very significant piece of the climate puzzle. Simply because of all the places on earth, trends in the long winter on the south pole would be most free from known dynamical effects. And this would be especially true for understanding the degree of CO2 inhibition of longwave energy loss.

More research seems to focus on the warming spots, such as Schneider’s 2010 work looking at just spring temperatures. Although very insightful, it is really only half, actually, 1/4th of the climate phenomenon. With a declining input of shortwave as observed via sunspot, and other solar proxies, I could justifiably conclude that there is a general global cooling trend with a dynamically induced warming trend that is superimposed, and likely due to the ocean’s “heat memory” that is then re-distributed by various Rossby waves.

This conclusion is further supported when I look at Epica CO2 data since 7-8000 years BP there is a steady rise from about 260 to 280. However in the Arctic from GISP2 temperature reconstructions I see a cooling trend that is in complete contradiction to the predicted effects of the CO2 trend. The GISP2 cooling trend is punctuated with periodic warmings, which would be expected in a dynamic oceanic climate. So again I must conclude that not only is the west Antarctic warming all dynamical but so it is very likely that most if not all the global warming trends.

A sustained global warming trend cannot be sustained dynamically, especially in the modern climate, unless you can find a way to permanently shift the mean albedo to a new state. This is especially clear when you look at the fact heat is going into the ocean and the direction of the TOA imbalance. There are interesting aspects to the bi-polar see saw pattern and ocean dynamics for abrupt climate change in the near past (see my post here on the Younger Dryas and LGM events); there are also interesting hypotheses concerning stochastic resonance (basically threshold processes in the presence of noise) which might be relevant to D-O events. Dr. Steig will be far better informed on the current state of these subjects, but your final conclusion in 40 does not follow and is demonstratably untrue in the modern case.

Purely radiatively, I think the “well-mixed” nature of CO2 is a bit overrated. It sure makes concentration measurements easier, but the radiative forcing and spatial response to that forcing from CO2 is not uniform. Over Antarctica, the TOA forcing for a doubling of CO2 can be much less and the surface forcing can be more than other regions. As Jianhua Lu noted, this is not completely separate from the dynamics, and he some papers (especially with Ming Cai) on the subject.

[Response: A good point. Even though CO2 is well-mixed, the corresponding radiative forcing is not, because the radiative forcing depends on the vertical temperature profile (among other things). In the Antarctic winter, this is an especially important issue, because of the strong surface inversion. –raypierre]

Chris (#41) “A sustained global warming trend cannot be sustained dynamically, especially in the modern climate, unless you can find a way to permanently shift the mean albedo to a new state.”

I agree that dynamically the trend sustained by a “static” ocean heat memory would not last much more than 40 years a la the models investigating natural variability showing .4C degree trendsfor 40 years ie Wigley et al 1990 . The trend in OHC via Argo will be telling which has greater impact: cooling solar or rising CO2.

Eric writes : ” Whether they would be *objectively* less compelling depends on the goodness of fit of statistics, and whether the those statistics are stationary.”

What arguments do you have that the statistics are indeed stationary?

[Response: Tim: No offense intended but please (please) read our paper, and O’Donnell et al. too, before asking me more questions at this level of detail. The short answer is that split verification statistics provide this evidence.–eric]

[Response: Are you honestly telling me you’ve been asking all these questions and you have *not* read the papers? Really?! GO TO THE LIBRARY (but in any case I’ve just emailed you a copy, probably breaking some law or other in doing so)–eric]

Eric writes : ” Are you honestly telling me you’ve been asking all these questions and you have *not* read the papers?”

If I had the papers to read then perhaps I could skip by some of these questions. Just “going to the library” every time I need to look up a paper isn’t really terribly practical unfortunately.

Thanks for sending it along though! Much appreciated.

Its just that you said “With no stations for verification in West Antarctica, it would be impossible to test stationarity” so if its impossible to test, then I figured you must have reasons for making the assumption. So one last question before reading the paper, is it impossible to test or not?

Jim, During the Antarctic winter, the Antarctic polar vortex forms. Like any cyclone, it prevents heat from reaching the center. Since the cyclone rages at near stratospheric altitude, and pulls air down from that level, and surface temperatures in the center of the vortex can thus get frightfully low.

Knowing this, one can easily imagine a number of reasons of a lowered South Pole temperatures during Antarctic winter, such as changing location of the center of the vortex, or it’s strength, both of which depend on a large number of chaotic factors.

However, there is one reason that you may find interesting since it is related to GHG concentrations. If you imagine the polar vortex as a cyclone that is essentially thermally isolated from the outside (apart from radiation), then it’s not hard to imagine that increased GHG concentrations will increase radiation to space, and thus cool down the area inside the vortex during the duration of winter months.

I am not sure if there have been any studies done on this effect, or if there are any other effects that would significantly offset it, but physically I find it very plausible that the increase of CO2 and methane concentrations could explain the cooling of the center of the polar vortex during the winter months.

TimtheToolman,
When you want to know if your kid has a fever, do you use a good ol’ mercury or alcohol thermometer or do you stand across the room with an IR sensor? What you seem not to understand is that no data set is perfect. The question is whether it is usable. If there are small gaps, you can fill them in. If there are unreliable readings, you can filter them out. Antartica is the toughest place on Earth for this kind of analysis as it is one of the few places on the planet that is undersampled rather than oversampled. However, that does not mean that the temperature time series carry no information. Again, what I am saying is that the datasets are complementary. You will get a more complete picture if you use both rather than either one. And they are independent, so the chances of spurious agreement in the trends are small.

I find myself agreeing with SM. It is nice to have a thread that is dominated by actual SCIENTIFIC controversy. And I would notice that while there is substantial disagreement, there is nowhere near the level of vitriol does not even approach the level where the disagreement is politically dominated.

[Response: Ray, thanks! I’ve said many times directly to the authors of O’Donnell et al. that I think they did a nice job with the paper. I mean it, despite my problems with it. Perhaps that is helping here.–eric]